It is often the case that related data may be stored in different data bases. For example, a bank may store related data such as account information, credit history, customer data, etc. in different data bases. It can be appreciated that over time related data associated with a particular account (i.e. a customer) may become inconsistent across the different data bases. As such, when data associated with the account is selected by a particular banking application from one of the data bases and processed, the end result may be incorrect because the selected data is not consistent with its associated data stored in the other data bases. As another example, in telephone applications different data that is related in some way, e.g. facility, provisioning, and maintenance data, may be stored in different data bases. If a person enters a subscription for telephone service, the facilities to implement the subscription are selected from a provisioning data base. However, the selected facilities may not actually be available. The reason for this may be, for example, that the facilities were marked unavailable due to maintenance activity and shown as such in the maintenance data base, but were inadvertently left marked as available in the provisioning data base. As such, a craftsperson would be unsuccessful implementing the requested service as a result of trying to use facilities that were not available. It can be appreciated that the problem of inconsistent data across multiple data bases may be both difficult and costly to correct.